Farzane Tajidini - Tabarestan University of Chalus, Chalus, Iran
Raziye Mehri - Deputy of Research and Technology, Ardabil University of Medical Sciences, Ardabil, Iran ۳ Department of Community Medicine, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran

Machine learning (ML) offers a quick and accurate prediction result, and it has developed into a potent tool in healthcare settings, providing stroke patients with individualized therapeutic care. Although there is a definite need for study, some research fields are not receiving adequate attention for scientific exploration despite the expanding use of ML and Deep Learning in healthcare. Therefore, the purpose of this work is to carefully review papers for each category after classifying state-of-the-art ML approaches for brain stroke into four groups based on their functionalities or similarities. The current study highlights the value of various ML techniques used in brain stroke.

_ Machine Learning, Brain Stroke, Prediction, CT pictures